The comparison of two prediction models for ureteral stones: CHOKAI and STONE scores

Accuracy of Quick Covid-19 Severity Index and Brescia-Covid Respiratory Severity Scale in Predicting ICU Admission and Mortality

“…Comorbid conditions were present in 37.5% patients. Although Diabetes mellitus (26.4%) and hypertension (17.9%) were the two most common conditions found in the present study, which is comparable with studies conducted elsewhere, our study found that diabetes mellitus was (26.4%) was the major comorbid condition, followed by hypertension (17.9%) (1,2,4,20) .Whereas, most of the other studies have reported that hypertension was leading comorbidity among COVID-19 patients (1,2,4,20) . (Table 1 ) https://ijpccr.com/ In the present study, more than half of total patients (51.5%) were treated in intensive care wards and overall in-hospital fatality was 25%.…”

“…In our study, prediction of in-hospital mortality by both qCSI and BCRSS risk models were found to be good with AUC of 0.761 and 0.760 respectively. The AUC of qCSI and BCRSS to predict in-hospital mortality in study conducted by Rohat AK et al, were 0.851and 0.842 respectively and in study conducted by Rodriguez-Nava G et al were 0.847 and 0.804 respectively (3,4) .…”

“…Corona virus disease 2019 (COVID- 19) pandemic has severe consequences in terms of exponentially high cases, disruption of health care system, imbalance in the 'demand and supply' chain of essential medical facilities, increased morbidity and mortality, particularly in the younger and middle-aged population (1)(2)(3)(4) . Developing countries like India experienced more catastrophic outcomes particularly in the second COVID-19 wave, due to limited and pre-existing inequitably distributed health-care infrastructure fighting against a very high healthcare demand across all the socioeconomic spectrum.…”

“…Limited number of emergency department beds and intensive care unit beds, high pressures to meet the rising demand of these facilities during pandemics can only be handled by efficient triaging, risk prediction and diagnostic workup and disposition. The risk screening tools in triaging and predicting the likelihood of adverse outcomes of COVID-19 patients at the first point of contact, would prevent overestimation or underestimation of severity risk in COVID pneumonia, that could potentially harm the patients due to suboptimal decisions regarding the clinical management (4,13,14) .…”

“…Various risk models have been developed for this purpose. Among which, two of them have gained particular interest (2,4) . The BCRSS algorithm (Brescia-COVID Respiratory Severity Scale) is a dynamic risk predictor, that uses the clinical parameters of patient to assess the need for escalating levels of respiratory support (non-invasive ventilation, intubation, proning) to suggest treatment recommendations.…”